From Generative AI-Supported Learning to Perceived Sustainability Judgment Capability in Accounting Education

Abstract

The rapid expansion of generative artificial intelligence (AI) is transforming higher education and creating new opportunities that are associated with the development of perceived professional competencies. At the same time, the accounting profession increasingly requires graduates who can evaluate sustainability disclosures and form informed judgments regarding sustainability-related information. However, limited research has examined how AI-supported learning relates to sustainability-oriented decision-making capabilities in accounting education. Drawing on Decision Support Systems (DSS) theory and constructivist learning theory, this study examines the associations between generative AI-supported learning and students’ perceived sustainability judgment capability. Specifically, the study investigates the mediating roles of perceived critical thinking and perceived sustainability knowledge, as well as the moderating role of AI literacy. A quantitative, cross-sectional research design was employed using self-reported survey data collected from 721 accounting students, and the proposed relationships were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings indicate that generative AI-supported learning is positively associated with students’ perceived critical thinking and perceived sustainability knowledge. In turn, both constructs show significant positive relationships with perceived sustainability judgment capability, with perceived sustainability knowledge demonstrating a stronger association. Additionally, AI literacy strengthens the relationships between generative AI-supported learning and the cognitive constructs. Importantly, the study captures students’ self-reported perceptions of their cognitive and judgment-related capabilities and does not assess objective cognitive performance or demonstrated judgment ability. The study contributes to the literature by positioning generative AI as an educational decision-support mechanism associated with perceived sustainability-oriented judgment capability through cognitive pathways, while highlighting the importance of aligning theoretical claims with perceptual measurement approaches.